Carbosmart is an innovative agriculture recommendation system that assists farmers in making sustainable decisions for their crops. The primary objective of Carbosmart is to help reduce carbon emissions in agriculture by up to 30%. The platform achieves this by providing farmers with personalized fertilizer recommendations and optimal nutrient amounts based on their specific crops and environmental conditions.

Carbosmart leverages the power of GPT-3 API, along with a Flutter framework and Python in backend, to offer a user-friendly and efficient experience for farmers seeking sustainable agricultural practices.

• Carbosmart aims to reduce carbon emissions by up to 30% in agriculture through optimized fertilizer recommendations and nutrient management.

• Utilizing GPT-3 API, Carbosmart provides accurate and tailored fertilizer recommendations for different crop types and growth stages.

• The platform calculates and suggests the ideal nutrient amounts required for crops, considering soil conditions, climate, and other environmental factors.

• The Flutter frontend offers a user-friendly interface that allows farmers to access the platform effortlessly and receive their recommendations promptly.

• Carbosmart seamlessly integrates with the GPT-3 API, enabling intelligent and natural language-based interactions with the system.

• By adopting Carbosmart's recommendations, farmers can practice sustainable agriculture and contribute to environmental conservation.

1. Clone the Carbosmart repository:

   git clone https://github.com/EDGARJN/carbosmart_app.git
   

2. Change directory to the Flutter project:

   cd carbosmart_app
   

3. Install Flutter dependencies:

   flutter pub get
   

4. Run the app on an emulator or connected device:

   flutter run
   

1. Install Python 3.x from the official website.

2. Clone the Carbosmart repository (if you haven't already).

3. Change directory to the Python backend:

   cd carbosmart_app/backend
   

4. Install Python dependencies:

   pip install -r requirements.txt
   

5. Start the Python server:

   python app.py
   

6. The backend server will run on http://localhost:5000.

1. Sign up for access to the GPT-3 API and obtain your API key.

2. Integrate the API key into the backend code (consult the GPT-3 API documentation for guidance).

1. Open the Carbosmart app on your device or emulator.

2. Input your crop type, growth stage, and environmental conditions.

3. Receive personalized fertilizer recommendations and optimal nutrient amounts.

4. Implement the suggested recommendations in your agricultural practices.

We welcome contributions from the open-source community. If you'd like to contribute to Carbosmart, please don't hesist to check us

Carbosmart is open-source software licensed under the MIT License. See the LICENSE file for more details.

• EDGAR JN - Mobile App Dev
• MGASA LUCAS - Backend and ML/AI Engineer
• DANFORD - Carbon based Data Collector and Analysis
• JUMA RUBEA - Carbon based Data Collector and Analysis
• BEATRICE - Project Manager and Business Analyst